MADT: Offline Pre-trained Multi-Agent Decision Transformer

Related tags

Deep Learning Offline-Pre-trained-Multi-Agent-Decision-Transformer
Overview

MADT: Offline Pre-trained Multi-Agent Decision Transformer

A link to our paper can be found on Arxiv.

Overview

Official codebase for Offline Pre-trained Multi-Agent Decision Transformer. Contains scripts to reproduce experiments.

image info

Instructions

It may be necessary to add the respective directories to your PYTHONPATH.

The offline smac dataset for this repo is available at here.

## password is vp1ulk

How to run experiments

  1. setup python environment with pip install -r requirements.txt
  2. to install StarCraft II & SMAC, you could run bash install_sc2.sh. Or you could install them manually to other path you like, following the official link: https://github.com/oxwhirl/smac.
  3. enter the ./sc2/ folder.
  4. set hyper-parameters in run_madt_sc2.py line 19-49 according to appendix.
  5. select a maps to test in envs/config.py line 142
  6. run the run_madt_sc2.py script
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Comments
  • Invalid link for the offline dataset

    Invalid link for the offline dataset

    Thanks to share your code for the interesting paper. I've tried to run your code by following the procedure written in README. However, the link to get the offline dataset for SMAC is not working. Could you update the link? or is there any other link to download the dataset?

    Regards,

    opened by aithlab 2
  • Torch version used?

    Torch version used?

    Thanks for the code. Nice paper. I am having some issues with the pytorch dataloader: what torch version did you use as it is not in the requirements.txt?

    opened by AsadJeewa 1
  • Offline dataset link is not available now?

    Offline dataset link is not available now?

    Thanks for your contribution for my project, but i could not access the offline dataset through the provided link. So I hope that maybe you can fix the issue. Thank you !!!!!

    opened by ChristianLin0420 0
Owner
Linghui Meng
Phd Candidate
Linghui Meng
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